"I believe that the industry will value brand awareness using the classic two metrics: reach and frequency for some time to come. Almost all the valuation methodologies and techniques today are based on the theory around reach and frequency. Unfortunately, the reach and frequency models all assume advertising that is shouting at consumers. Today we can't afford to just shout, we have to listen too. I have seen a significant uptick in the number of campaigns that are also tracking both share of voice (through buzz and sentiment) and of course shares/likes/forwards.

Reach and frequency measure how effective is your shouting. Share of voice and social sharing measure how effectively are you engaging. I believe you need all 4 to enhance brand awareness. For this to work in an automated buying environment, you need to be able to factor these elements into your bid strategy. That means slicing these metrics along your audience segmentation, then developing bid hypotheses, testing them, and refining them in that same context."

"For too long, the industry has depended on metrics for brand that are inadequate. That is rapidly changing.
At the early stages (and amazing still today) many brands looked at DR measures like clickthrough rates as brand proxies. As has been proven many times in recent years, clickthrough rates are actually poor metrics as proxies for almost any campaigns, even DR, let alone brand. View throughs have been another proxy for branding. The argument (whether you agree that the view happened is a result of a web impression or other contact with the consumer), is that a view through customer must know something about the brand.

But today, we have real brand analytics. The classic brand analytics are awareness (aided or unaided) and brand lift (intent to purchase).

Vizu launched an enterprise level platform last year that is affordable enough to be always plugged in for a major advertiser. Dynamic Logic and Insight Express have answered with similar products. And I am certain that others are on the horizon. These metrics mirror the classic P&G annual research. They are just always on and can provide site by site metrics in real or near real time, assuming a large enough campaign.

There is no reason to consider less perfect metrics when the ideal (for a reasonable price) is available now."

"First let’s start with building and measuring brand health. “Awareness” is a pretty broad metric. The most complete set of measures put forth is probably the venerable Y&R Brand Asset Valuator (BAV), which was established in the early 90's as a comprehensive set of measurements which tracks differentiation, relevance, esteem and Knowledge. To achieve knowledge, a media plan needs to generate reach. To be relevant, messaging needs to reach the right audiences at the right time through frequency oversight. And media strategies help build esteem and differentiation through a blend of right messaging/right audience.

The universal measure for brand health is reach/frequency, and especially effective frequency because it’s the metric that allows planners communication flow oversight with audiences and messages. Ultimately, knowing reach/frequency levels, the duplication (“overlap”) and the frequency distribution across messaging, channels and audience is the bridge to understand and affect brand awareness.

Automated media buying platforms vastly improve on the speed of knowledge and span of control, and provide the planner with the ability to steward the plan in real-time. Coupled with real-time surveys such as KN Dimestore, planners can both measure and manage their brand’s reach/frequency and collect critical brand metrics that ladder up to differentiation, esteem, relevance and knowledge."

"It may seem obvious, but tracking the cost of your media in an automated buying environment is paramount. While there is certainly value to be found, lackluster management will lead to bloated costs and inefficient
media placements.

So what exactly are we paying for? While a long term perspective, I believe the metric that will have the most impact on digital buying in the next five years is the 'viewable' impression. Deploying technology like RealVu gives us insight into how many of our served ad impressions are actually being seen. Buyers will be able to quickly identify pockets of value within the market and bid accordingly, minimizing waste and maximizing value.

Of course, we can't stop running media while the industry sorts itself out. For now, the strongest way to measure digital media success is with qualitative research. Because the medium is inherently trackable, we often get caught up in the sheer volume of data we collect. However, without implementing a brand study along your buy, most metrics live in isolation. Layering a brand study allows us to identify metrics that lead to awareness and affinity lift, and reallocate budgets to promote those behaviors."

"The real answer brands want is WHY things are happening and HOW a brand can better excite consumers through advertising. Focus on the brand exciting consumers... The key metrics that need to be tracked for brand awareness campaigns in an automated buying environment includes traditional quantitative analysis such as reach . More importantly, qualitative analysis is needed to determine if the intended audience was reached in a receptive state, moving the brand needle. For example, brand mentions and share of voice relative to the perception change the brand was trying to create; engagement with distributed content plus time spent with it, and brand studies & respondent surveys. The bigger question to answer is 'what is a brand trying to do?' so you can serve up metrics that explain more then just the numbers and ultimately build brand equity."

"The key metrics for brand campaigns in automated environments should be the same as they are in 'traditional' buying environments. The 3 most popular ones that we see are brand recall, affinity and purchase intent.

While the measurement methodologies are well known, there are obviously non-trivial technical challenges to leverage them in meaningful ways within automated buying environments. Perhaps the largest challenge is setting up a direct feedback loop, where the brand metrics can be directly translated into media buying instructions. The most direct way we have seen this done is on an audience level in automated platforms where data and inventory are synchronized.

That being said, CTR is often the #1 brand reference for automated platforms. For some campaigns, i.e. driving engagement, it makes sense. But most of the time, this is due to the fact that CTR is the only ubiquitous metric that can be acted on directly without some level of technical setup."

"Branding is as tricky to measure as it is to define. For the purposes of digital, and because we can often get so bogged down in over-measurement of DR, let’s say branding efforts seek to affect consumers in ways beyond those immediately and commercially attributable. That is to say: branding takes time and can be tough to measure.

In the case of branding, it helps to ask questions about whether the consumer is even truly seeing the ad, and if so, if he is being affected by it. It is this effect that becomes important to measure. A click has, for a long time, been a point of leap for us. If someone clicked on my ad, he must be interested; the ad must have done its job. While there is truth to this, it leaves out a large chunk of advertising’s power, the power to change perceptions. Relying only on actions such as a click or a site conversion is not sufficient to gauge this very important effect.

To my mind, then, the main metric to this end is brand lift by survey. A properly executed brand study can shed a good deal of light on just how well your creative and strategy have influenced users’ ideas and opinions about the advertiser or product. Secondary to this are engagement tools, such as video or rich media, which can measure a user’s interaction with your brand. This does, however, still necessitate an action to be taken, leaving out passive influence, which is perhaps synonymous with branding."

For awareness campaigns, the prevailing standard is brand surveys that directly ask about awareness, then spit back results anywhere from 4 weeks to 9 months later. Where does that leave digital's greater opportunity to track and optimize?

A huge driver of automated buying is machine learning that feeds real time optimization - a capability heavily used for direct response. Now, real time auto-optimization off survey responses can take branding to the next level. Buying platforms have started to integrate with brand study vendors who feed "conversion" signals to prediction algorithms for questions on unaided brand awareness, brand favorability, and awareness of product attributes.

Short of brand surveys, we're rich in awareness proxies measurable online. Time spent with a custom site integration, rich media interaction, and Facebook likes are all appropriate given specific objectives. But the challenges are: 1) proving correlation to awareness, and 2) incorporating into auto-optimization."

Every client is different, and both the vertical and overall strategic marketing objectives of the end client should be the deciding factors in choosing a KPI for brand awareness. Despite these dependencies, there are some universally applicable rules for how you should execute success measurement for a brand awareness initiative:

If the objective is not a back-end metric that you can track via an ad server, always contract with a 3rd party brand measurement provider. (A buyer with a brand measurement product is not one big, all inclusive solution. Its one big conflict of interest.)

Your provider’s solution should be implemented at the ad server level (no exceptions), and must be able to measure your KPI across the entire media plan. (direct buys, networks, DSPs, ATDs, etc.)

Your provider should give you real-time insight into how different buyers on a plan are performing against your KPI (What’s the point of RTB if you can’t get RT-insights?)

Of course, there are innumerable other factors to consider when selecting a brand awareness metric and provider. With that said, following these three basic rules will go a long way towards ensuring fluid execution, accurate measurement, and measurable success for your client’s brand awareness initiatives.

3 Comments

What a loaded question...how can there be three universal KPIs for digital brand campaigns? I'm not buying it.

The reason is that it depends on the specific campaign objectives - the answer(s) could be any or all of the above suggestions. Therefore - all of these esteemed panelists are right; and you can claim your special gold star by emailing John E.

Seriously though, a better conversation might be about forcing a primary KPI from which to optimize (manually or otherwise).

Last, since the title includes "in an automated buying environment," I'm going to assume this means data-driven buying. With that qualification we should all be thinking about LTV and "share of customer" (in the Peppers & Rodgers way).

It's important to distinguish between campaign delivery metrics and brand metrics. They are very different things.
Delivery metrics include impressions, GRPs, share of voice, reach, frequency, unique users, clicks, click through rates and cost per click. These measures can largely be collected and reported electronically, often without consumers’ direct knowledge. These are not brand metrics.
Brand metrics are altogether different. These relate to how marketing communications change perceptions of a brand in mind of the consumer. Remember, 'brands' are basically perceptions of a particular product or service held by the consumer. "Brand health" is a measure of how positively consumers view your product or service. All this means brand measures can only be established by asking consumers what they think or feel about a product or service and tracking how those perceptions change over time or before or after an advertising campaign.